Marvin Minsky
(39 articles)
SNARC
Stochastic Neural Analog Reinforcement Calculator
Stochastic Neural Analog Reinforcement Calculator
Recognized as one of the earliest electronic neural network machines, SNARC simulated a rat navigating a maze using analog components and probabilistic logic.
Generality: 645
Natural Language Problem
Challenges encountered in understanding, processing, or generating human language using computational methods.
Generality: 875
Task Environment
Setting or context within which an intelligent agent operates and attempts to achieve its objectives.
Generality: 760
Knowledge Representation
Method by which AI systems formalize and utilize the knowledge necessary to solve complex tasks.
Generality: 890
Symbolic Computing
A paradigm in AI that uses symbolic representations of problems and logic-based reasoning to perform computational tasks and solve complex problems.
Generality: 795
Human-Level AI
AI systems that can perform any intellectual task with the same proficiency as a human being.
Generality: 945
Symbolic AI
Also known as Good Old-Fashioned AI (GOFAI), involves the manipulation of symbols to represent problems and compute solutions through rules.
Generality: 830
AGI
Artificial General Intelligence
Artificial General Intelligence
AI capable of understanding, learning, and applying knowledge across a wide range of tasks, matching or surpassing human intelligence.
Generality: 905
Search
The process within AI of exploring possible actions or solutions in order to achieve goals or solve problems.
Generality: 890
Memory Systems
Mechanisms and structures designed to store, manage, and recall information, enabling machines to learn from past experiences and perform complex tasks.
Generality: 790
Internal Representation
The way information is structured and stored within an AI system, enabling the system to process, reason, or make decisions.
Generality: 845
Machine Understanding
Capability of AI systems to interpret and comprehend data, text, images, or situations in a manner akin to human understanding.
Generality: 828
Linear Separability
The ability of a dataset to be perfectly separated into two classes using a straight line in two dimensions or a hyperplane in higher dimensions.
Generality: 500
Agent
System capable of perceiving its environment through sensors and acting upon that environment to achieve specific goals.
Generality: 790
GOFAI
Good Old-Fashioned AI
Good Old-Fashioned AI
Traditional approach to AI that relies on symbolic reasoning, logic, and rule-based systems to simulate intelligent behavior.
Generality: 815
Recursive Self-Improvement
Process by which an AI system iteratively improves itself, enhancing its intelligence and capabilities without human intervention.
Generality: 790
Silicon-Based Intelligence
Concept of artificial intelligence systems that operate on silicon-based hardware, contrasting with biological, carbon-based forms of intelligence such as humans.
Generality: 777
Frame Problem
Challenge in AI of representing and updating the effects of actions in a dynamic world without having to explicitly state all conditions that remain unchanged.
Generality: 625
Perceptron Convergence
A phenomena where a perceptron algorithm effectively stabilizes, ensuring that it can find a solution for linearly separable datasets after a finite number of iterations.
Generality: 500
NLU
Natural Language Understanding
Natural Language Understanding
Subfield of NLP focused on enabling machines to understand and interpret human language in a way that is both meaningful and contextually relevant.
Generality: 894
Production System
A framework used in AI for automated problem-solving that consists of a set of rules and data, enabling systematic exploration of possible actions to achieve a goal state.
Generality: 725
Cognitive Architecture
A theory or model that outlines the underlying structure and mechanisms of the human mind or AI systems, guiding the integration of various cognitive processes.
Generality: 850
Grounding
Process of linking abstract symbols or data representations to real-world meanings or experiences, enabling the system to understand and act based on those symbols in a meaningful way.
Generality: 755
Dualism
Theory or concept that emphasizes the division between symbolic (classical) AI and sub-symbolic (connectionist) AI.
Generality: 830
Reasoning System
Software entities designed to emulate human reasoning processes by drawing logical inferences from available data or known facts.
Generality: 775
AI Winter
Periods of reduced funding and interest in AI research and development, often due to unmet expectations and lack of significant progress.
Generality: 525
Commonsense Reasoning
The ability of AI systems to make presumptions about the type of
Generality: 775
State Representation
The method by which an AI system formulates a concise and informative description of the environment's current situation or context.
Generality: 682
Autonomous Learning
Systems capable of learning and adapting their strategies or knowledge without human intervention, based on their interactions with the environment.
Generality: 870
AI Effect
Phenomenon where once an AI system can perform a task previously thought to require human intelligence, the task is no longer considered to be a benchmark for intelligence.
Generality: 770
Superintelligence
A form of AI that surpasses the cognitive performance of humans in virtually all domains of interest, including creativity, general wisdom, and problem-solving.
Generality: 850
Narrow AI
Also known as Weak AI, refers to AI systems designed to perform a specific task or a narrow range of tasks with a high level of proficiency.
Generality: 760
WBE
Whole Brain Emulation
Whole Brain Emulation
Hypothetical process of scanning a biological brain in detail and replicating its state and processes in a computational system to achieve functional and experiential equivalence.
Generality: 540
Cognitive Computing
Computer systems that simulate human thought processes to solve complex problems.
Generality: 900
Autonomous Reasoning
Capacity of AI systems to make independent decisions or draw conclusions based on logic or data without human intervention.
Generality: 850
1-N Systems
Architectures where one input or controller manages multiple outputs or agents, applicable in fields like neural networks and robotics.
Generality: 790
Shared Awareness
Collective understanding and perception of information among multiple agents, both human and machine, in a given environment.
Generality: 500
Self-Correction
An AI system's ability to recognize and rectify its own mistakes or errors without external intervention.
Generality: 815
Agentic AI Systems
Advanced AI capable of making decisions and taking actions autonomously to achieve specific goals, embodying characteristics of agency and decision-making usually associated with humans or animals.
Generality: 775